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JD Cloud Developers

JD Cloud Developers (Developer of JD Technology) is a JD Technology Group platform offering technical sharing and communication for AI, cloud computing, IoT and related developers. It publishes JD product technical information, industry content, and tech event news. Embrace technology and partner with developers to envision the future.

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Latest from JD Cloud Developers

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JD Cloud Developers

May 26, 2026 · Artificial Intelligence

AI‑Powered Oxygen Vision Slashes Cross‑Border E‑Commerce Image Production Cost and Time

The article details how JD’s Oxygen Vision uses AI to automatically generate compliant, localized product image sets for multiple overseas platforms, reducing SKU‑level creation time from days to minutes, cutting costs by up to 90%, and addressing challenges of multi‑language, cultural, and regulatory adaptation.

AI image generationCost Reductionautomation

0 likes · 15 min read

AI‑Powered Oxygen Vision Slashes Cross‑Border E‑Commerce Image Production Cost and Time

JD Cloud Developers

Apr 14, 2026 · Mobile Development

How Taro’s Custom iOS Rendering Layer Achieves High‑Performance Cross‑Platform UI

This article details Taro’s self‑developed iOS rendering layer and TaroUI framework, explaining how a double‑thread pipeline, native‑view‑plus‑layer architecture, rich‑text engine, and extensive rendering optimizations deliver high performance, stability, and cross‑platform consistency for mobile applications.

PerformanceTaroUI framework

0 likes · 19 min read

How Taro’s Custom iOS Rendering Layer Achieves High‑Performance Cross‑Platform UI

JD Cloud Developers

Apr 8, 2026 · Artificial Intelligence

How JoyAI-Image-Edit Brings Spatial Intelligence to Open‑Source Image Editing

JoyAI-Image-Edit, an open‑source multimodal foundation model from JD Research Institute, integrates text‑to‑image generation, image understanding, and instruction‑driven spatial editing, achieving world‑leading spatial perception and editing capabilities that unlock new applications across e‑commerce, robotics, 3D reconstruction, and design.

Generative Modelscomputer visionimage editing

0 likes · 7 min read

How JoyAI-Image-Edit Brings Spatial Intelligence to Open‑Source Image Editing

JD Cloud Developers

Mar 23, 2026 · Artificial Intelligence

OpenClaw Deep Dive: Turning LLMs into Actionable AI Agents

This article provides a comprehensive technical analysis of OpenClaw, an open‑source autonomous‑agent framework that integrates large language models with local system operations through a four‑layer architecture, detailed message‑processing steps, ReAct reasoning loops, security mechanisms, performance optimizations, and real‑world application scenarios.

AI agentsLLM integrationOpenClaw

0 likes · 13 min read

OpenClaw Deep Dive: Turning LLMs into Actionable AI Agents

JD Cloud Developers

Mar 17, 2026 · Backend Development

How to Build a MyBatis Plugin to Throttle Burst SQL Traffic and Protect Your Database

This article explores the challenges of sudden traffic spikes that overload applications and databases, and presents a step‑by‑step design, implementation, and optimization of a MyBatis plugin that intercepts SQL, applies fingerprint‑based rate limiting, and integrates with Joycode for rapid development and testing.

Database protectionJavaMyBatis

0 likes · 10 min read

How to Build a MyBatis Plugin to Throttle Burst SQL Traffic and Protect Your Database

JD Cloud Developers

Mar 16, 2026 · Operations

Why Traditional Monitoring Fails for AI Supercomputing and How to Build Next‑Gen Intelligent Monitoring

In the era of hundred‑thousand‑GPU clusters and trillion‑parameter models, conventional monitoring can no longer rely on simple alerts; it must become an observability system that quantifies training and inference performance, breaks data silos across data centers, servers, and networks, and provides business‑aware insights for AI infrastructure.

AI infrastructureLarge Models

0 likes · 10 min read

Why Traditional Monitoring Fails for AI Supercomputing and How to Build Next‑Gen Intelligent Monitoring

JD Cloud Developers

Mar 3, 2026 · Mobile Development

How to Integrate AI into Mobile Apps Without Sacrificing User Experience

This article examines the practical challenges of adding AI features to mobile clients, highlighting device fragmentation, performance trade‑offs, user pain points, and a layered approach that balances lightweight models, graceful degradation, and edge‑cloud collaboration to keep the experience smooth for the majority of users.

AI integrationAR gesturesMobile Development

0 likes · 15 min read

How to Integrate AI into Mobile Apps Without Sacrificing User Experience

JD Cloud Developers

Mar 2, 2026 · Artificial Intelligence

How AI Agents Are Revolutionizing Insurance: Methodology, Economics, and Technical Blueprint

This comprehensive guide explains how AI agents can be selected, designed, and deployed across the insurance supply chain, detailing their economic impact, technical architecture—including domain‑specific large models, knowledge bases, planning strategies, and reinforcement‑learning loops—and outlines future roadmaps for pricing, fulfillment, and risk‑control automation.

AI agentArtificial IntelligenceInsurance

0 likes · 43 min read

How AI Agents Are Revolutionizing Insurance: Methodology, Economics, and Technical Blueprint

JD Cloud Developers

Feb 4, 2026 · Artificial Intelligence

How Deep Research Transforms LLMs into Autonomous AI Researchers

This article examines Deep Research, an AI system that adds autonomous planning and deep reasoning to large language models, enabling them to browse the web, perform long‑chain reasoning, and generate professional, citation‑rich reports for complex tasks such as industry trend analysis and technical competitive research.

AI researchLLMReAct

0 likes · 22 min read

How Deep Research Transforms LLMs into Autonomous AI Researchers

JD Cloud Developers

Jan 30, 2026 · Artificial Intelligence

Scaling Generative Recommendation: Inside JD’s 9N-LLM Multi‑Framework Training Engine

This article details JD Retail’s 9N-LLM unified training engine, which integrates TensorFlow and PyTorch across GPU and NPU hardware to tackle the massive data, model size, and reinforcement‑learning complexities of generative recommendation, offering concrete components, performance benchmarks, and future directions.

GPU/NPUPyTorchTensorFlow

0 likes · 26 min read

Scaling Generative Recommendation: Inside JD’s 9N-LLM Multi‑Framework Training Engine